Challenges associated with identification, understanding, and modeling of interactions in ecological systems are present at every level of complexity from ecological genomics to landscape ecology. Interactions in ecology have a dual meaning. In a statistical sense they mean that the effect of one predictor variable depends in some way on the value of another. In an ecological sense, they refer to connections among different sets of ecosystem components such as resources and species or even genes and environments. Both types of interactions pervade ecological data sets, and their representation warrants attention. For example, the shape of an empirical response pattern is an emergent property of a system and can yield important information about underlying interactions. Yet, through our choice of analytical tools, we seldomly acknowledge the spectrum of shapes that can arise from complex data structure. Hence, we can lose touch with the behavior of contributing factors. Ecology intersects with the study of complex systems, and our toolboxes must grow to meet interdisciplinary needs.